Complexity resource manager for multi-channel speech processing

ABSTRACT

A multi-channel speech processor for encoding speech in a packet network environment is disclosed. In one illustrative aspect, a complexity resource manager (CRM) is executed by a controller or processor. The CRM manages the level of complexity of encoding which is used by a signal processing unit (SPU) to convert the speech signal into packet data. In general, the CRM determines the level of complexity of encoding based on a calculated complexity budget, where the complexity budget is determined based on the time required to process prior speech signal channels and the time available to process the remaining channels. In this way, the CRM is able to control the overall complexity of the speech processor through its ability to signal the SPU to encode speech signal in a complexity reduced mode based on the calculated complexity budget under certain conditions.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates generally to speech and audio signalprocessing. More particularly, the present invention relates tocomplexity resource management for multiple channel speech and audiosignal processing.

2. Related Art

In recent years, packet-based networks, such as the Internet, have begunto replace traditional telephone networks (i.e., switched networks) fortransportation of voice and data in accordance with voice-over-packet(“VoP”). The packetizing of voice signals for transmission over a packetnetwork has been recognized as a less expensive, yet effective,alternative to traditional telephone service. For example, with theemergence of voice over IP (“VoIP”), telephone conversations may now becaptured, packetized and transported over the Internet. Other examplesof emerging VoP implementations include Next Generation Networks(“NGN”), which do not necessarily use the Internet Protocol (IP) for thetransmission of packet voice.

In a conventional VoIP system, telephone conversations or analog voicemay be transported over the local loop or the public switched telephonenetwork (“PSTN”) to the central office (“CO”), where speech is digitizedaccording to an existing protocol, such as G.711. From the CO, thedigitized speech is transported to a gateway device at the edge of thepacket-based network. The gateway device receives the digital speech andpacketizes it. The gateway device can combine G.711 samples into apacket, or use any other compressing scheme. Next, the packetized datais transmitted over the Internet using the Internet Protocol forreception by a remote gateway device and conversion back to analog voicein the reverse manner as described above.

For purposes of this application, the terms “speech coder” or “speechprocessor” will generally be used to describe the operation of a devicethat is capable of encoding speech for transmission over a packet-basednetwork and/or decoding encoded speech received over the packet-basednetwork. As noted above, the speech coder or speech processor may beimplemented in a gateway device for conversion of speech samples into apacketized form that can be transmitted over a packet network and/orconversion of the packetized speech into speech samples. Ordinarily, agateway processor handles the speech coding of multiple channels.

Efforts have been made to increase the efficiency and operation ofspeech processors to encode speech for transmission over packet-basednetworks. One area of development has been in the area of speech codecs.For example, recent speech codecs, such as the adaptive multi-rate(AMR), the enhanced variable rate speech coder (EVRC), and theselectable mode vocoder (SMV), have been designed for a best tradeoffbetween bit-rate, complexity and quality for their designedapplications. In order to provider better playback quality at a lowerbit-rate, these modern codecs are generally more complex and thereforerequire more processing power than lower-complexity high-bit-rate speechcodecs, such as G.711. As a result of the increased complexity of thesecodecs and the associated hardware requirements, the channel density(i.e., number of channels) that a speech processor (or gateway) cansupport is limited. Increasing the processing power of speech processorsand gateways to handle higher complex codecs would involve a substantialincrease in cost and investment. On the other hand, operatinglower-complexity high-bit-rate codecs results in increased bit rate andreduced throughput over the communication channels. In addition, inaccordance with certain communication standards, low-bit-rate complexcoders are mandatory, and therefore use of lower complexity codecs isnot possible.

Speech encoding algorithms executed by speech processors (and gateways)have also been enhanced to increase the efficiency and operation of thecommunication channel. In particular, variable rate codecs wereintroduced for packet networks, where the average load on the networksis an essential factor in their operation. According to these enhancedencoding algorithms, the bit rate used to encode a speech signal may beselected according to the input speech. For example, approximately fiftypercent (50%) of conversational speech involves inactive speech(silence). Typically, higher complex encoders are used to encode activespeech segments with a somewhat higher bit rate, while lower complexityencoders are used to process silence or background noise (inactivespeech) segments at a lower bit rate. Although this solution is suitablefor the network due to its performance being related to the average bitrate, the processing of these multi-channels of speech by a DSP isparticularly challenging, since the throughput of a DSP is not definedby the average complexity, but by the maximum complexity. Although, onthe average, a DSP may be able to handle all the channels, since at agiven time some channels carry active speech—that need higher complexityalgorithm—and others carry inactive speech—that need lower complexityalgorithm, there may still be instances where a majority or all channelsinvolve active speech and, thus, all such channels needing highercomplexity algorithm, which together will exceed the availablecomputation power of the DSP.

Accordingly, there is a need in the art for a speech coder apparatus andmethod, which overcomes these and other shortcomings of presentimplementations for encoding voice information into a packetized formthat can be transmitted over a packet network.

SUMMARY OF THE INVENTION

In accordance with the purposes of the present invention as broadlydescribed herein, there is provided a multi-channel speech processor forencoding speech for a packet network environment. In one illustrativeaspect of the present invention, a complexity resource manager (CRM) isexecuted by a controller or processor. The CRM manages the level ofcomplexity of the coding, which is used by a signal-processing unit(SPU) to convert the speech signal into packet data. In someembodiments, the CRM may also be used to manage the decoding operationas well. In general, the CRM determines the level of complexity of thecoding based on a calculated complexity budget, where the complexitybudget is determined based on the time consumed to process prior speechsignal channels and the time available to process the remainingchannels. In this way, the CRM is able to control the overall complexityof the speech processor, and adjust the speech processor to meet thecomplexity budget, through its ability to signal the SPU to encodeand/or decode a speech signal in a complexity reduced coding mode basedon the calculated or consumed complexity budget.

For example, the speech processor may use the SMV codec to encode speechsignals for a plurality of channels 1 through m. The SMV codec mayprovide four coding rates, each rate having an associated level ofcomplexity including: a full rate, a half rate, a quarter rate, and aneighth rate, for example. It is possible that the SMV full rate, thequarter rate, and the eighth rate schemes are less complex than the SMVhalf rate scheme due to the more intense search required to execute thehalf rate scheme. In this example, the CRM may choose a coding rate fora given channel “n”, based on the time spent processing channel 1through n−1 and the available processing time left to process channels nthrough m. Thus, the CRM may select a lower level complexity rate (e.g.,full rate, quarter rate, or eighth rate) to process a given speechsignal channel n (or groups of channels “n+o”, where “n+o”≦m) where thecalculated processing time left to process the remaining channels wouldnot be sufficient to support a higher level complexity coding rate(e.g., SMV half-rate). It is noted that although described in terms ofordinal numbers n for channels 1 through m, the speech processor of thepresent invention may actually process speech signals for channels 1through m in any order as input signals arrives. It would also bereadily apparent to one skilled in the art having the benefit of thisdisclosure that other speech codecs having coding rates of variouscomplexity can also benefit from the CRM.

In accordance with other embodiments, the CRM is configured to signalthe SPU to encode a speech signal based on a complexity level, ratherthan a specific rate. For example, the CRM may signal the SPU to switchto a higher or lower complexity algorithm, or to use a higher or lowercomplexity path in a particular algorithm, based on the complexitybudget.

Typically the speech processor also executes a speech encoder algorithmfor the common processing of channel speech signals, generally executedin conjunction with the CRM by the controller or implemented as acomponent of the CRM. As noted above, the encoder algorithm may be usedto define the appropriate complexity coding rates corresponding toactive speech segments and inactive speech segments, for example. Whenthe CRM defines a lower complexity coding rate than the encoderalgorithm in accordance with the complexity budget, the coding rateselected by the CRM overrides the rate selected by the encoder algorithmas is used by the SPU. Where the CRM does not define a coding rate(e.g., where the complexity budget would allow the remaining channels tobe processed at the highest complexity rate) or where the complexitycoding rate selected by the encoder algorithm is of less complexity thanthat defined by the CRM, the coding rate selected by the encoderalgorithm is used by the SPU to process a given speech signal.

It is noted that the calculation of the overall complexity budget mayalso take into account the processing power consumed by other commonprocesses (e.g., tone detection, echo cancellation).

In certain embodiments, the CRM may calculate the complexity budgetbased on groups of channels processed. For example, suppose the speechprocessor is capable of interfacing with sixty (60) communicationchannels. In this 60-channel example, the CRM may evaluate thecomplexity budget in four (4) groups of fifteen (15) channels, six (6)groups of (10) channels, or other various arrangement of groups ofchannels. Thus, the complexity budget may be calculated after the first15 channels have been processed to determine the complexity rate for thenext 15 channels. Likewise, the complexity budget may be calculatedafter the first 30 channels have been processed to determine thecomplexity rate for the next 15 channels, and so on.

According to another aspect of the present invention, the speechprocessor may be used to support a variable number of channels. In thisembodiment, the CRM may determine whether an additional requestedchannel may be supported based on the calculated complexity budgetand/or in accordance with certain quality requirements. For example,where the CRM determines that the available processing time left issufficient to process all currently accepted or active channels and therequested channel, the CRM may accept the requested channel forprocessing by the SPU. Otherwise, if the available processing time leftis not sufficient to process all currently accepted or active channelsas well as the requested channel, the CRM denies the requested channel.In other embodiments, the CRM may be configured to accept the requestedchannel only if the quality of output of the active channels would notbe severely impacted or fall below a certain threshold.

Variable channel support may be implemented in a number of ways. In someembodiments, a pre-determined number of channels are supported. In thisembodiment, the CRM will accept a channel if the pre-determined numberof channels have not been exceeded (i.e., the CRM is currently managingfewer than the pre-determined number of channels). Otherwise, the CRMwill reject the requested channel. In other embodiments, acceptance of arequested channel involves first determining whether the SPU is able torun without any complexity reduction (e.g., up to N channels). If so,the CRM does not operate, and any requested channel can be accepteduntil N channels have been accepted. For each requested channel above Nchannels, the CRM performs statistical complexity reduction analysis.For example, the CRM may determine the level of complexity reductionneeded to accommodate the requested channel, and may accept/reject therequested channel based on whether a certain threshold of complexityreduction will be exceeded.

According to yet another aspect of the present invention, the speechprocessor may support multiple codecs which are stored in a memorycoupled to both the controller and the SPU. According to thisembodiment, multiple speech codecs (e.g., AMR, EVRC, SMV, G.711) may besupported by the speech processor to provide wider support of speechcoders. In operation, the controller loads the coder which correspondsto the input speech signal into the SPU for processing the speech signalwhile the CRM may define the level of complexity for the particularcoder as described above.

These and other aspects of the present invention will become apparentwith further reference to the drawings and specification, which follow.It is intended that all such additional systems, methods, features andadvantages be included within this description, be within the scope ofthe present invention, and be protected by the accompanying claims.

BRIEF DESCRIPTION OF THE DRAWINGS

The features and advantages of the present invention will become morereadily apparent to those ordinarily skilled in the art after reviewingthe following detailed description and accompanying drawings, wherein:

FIG. 1 illustrates a block diagram of a packet-based network in whichvarious aspects of the present invention may be implemented;

FIG. 2 illustrates a block diagram of a multi-channel speech processorin accordance with one embodiment;

FIG. 3 depicts an illustrative flow diagram of a speech encoding methodutilizing a complexity resource manager in accordance with oneembodiment; and

FIG. 4 depicts an illustrative flow diagram of a speech encoding methodsupporting variable communication channels in accordance with oneembodiment.

DETAILED DESCRIPTION OF THE INVENTION

The present invention may be described herein in terms of functionalblock components and various processing steps. It should be appreciatedthat such functional blocks may be realized by any number of hardwarecomponents and/or software components configured to perform thespecified functions. For example, the present invention may employvarious integrated circuit components, e.g., memory elements, digitalsignal processing elements, logic elements, and the like, which maycarry out a variety of functions under the control of one or moremicroprocessors or other control devices. Further, it should be notedthat the present invention may employ any number of conventionaltechniques for data transmission, signaling, signal processing andconditioning, speech coding and decoding and the like. Such generaltechniques that may be known to those skilled in the art are notdescribed in detail herein.

It should be appreciated that the particular implementations shown anddescribed herein are merely exemplary and are not intended to limit thescope of the present invention in any way. For example, although thepresent invention is described utilizing the SMV speech coder, it shouldbe noted that the present invention may be implemented with other speechcoders having rates of various complexity. Indeed, for the sake ofbrevity, conventional data transmission, speech encoding, speechdecoding, signaling and signal processing and other functional aspectsof the data communication system (and components of the individualoperating components of the system) may not be described in detailherein. Furthermore, the connecting lines shown in the various figurescontained herein are intended to represent exemplary functionalrelationships and/or physical couplings between the various elements. Itshould be noted that many alternative or additional functionalrelationships or physical connections may be present in a practicalcommunication system.

FIG. 1 depicts an illustrative communication environment 100 that iscapable of supporting the transmission of packetized voice information.Packet networks 110, such as those conforming to the Internet Protocol(“IP”), may support Internet telephony applications that enable a numberof participants 104, 114 to conduct voice communication in accordancewith VoP techniques. Network 102, which may be a non-packet network,such as switched network, or PSTN, supports telephone conversationsbetween participants 104. In a practical environment 100, network 102may communicate with conventional telephone networks, local areanetworks, wide area networks, public branch exchanges, and/or homenetworks in a manner that enables participation by users that may havedifferent communication devices and different communication serviceproviders. In addition, in FIG. 1, participants 104 of switched network102 may communicate with other participants 114 of other packet networks110 via gateway 106.

Speech processor 108 of gateway 106 converts conventional voiceinformation of participants 104 of network 102 into a packetized formthat can be transmitted to the other packet networks 110. A gateway is asystem which may be placed at the edge of the network in a centraloffice or local switch (e.g., one associated with a public branchexchange), or the like. It is noted that in addition to the speechencoding and decoding, the gateway performs various functions ofreceiving and transmitting information (speech samples) from theswitched network 102, and receiving and transmitting information (speechpackets) from the packet network (e.g., padding and stripping headerinformation). The gateway also performs data (modem, fax) transmissionand receiving functionalities. It will be appreciated that the presentinvention can be implemented in conjunction with a variety of gatewaydesigns. A corresponding gateway and a speech processor (not shown)might also be associated with each of the other networks 110, and theiroperation is substantially the same manner as described herein forgateway 106 and speech processor 108 for encoding speech informationinto packet data for transmission to other packet networks. It is alsopossible that participants 114 generate packetized speech, where nogateway or additional speech processing is needed for the communicationof participants 114 to the networks 110.

Speech processor 108 of the present invention is capable of interfacingwith a plurality of communication channels (e.g., 1 through m channels)via communication lines 112 for receiving speech signals as well ascontrol signals in network 102. For example, speech signals fromparticipants 104 are communicated via an appropriate channel forprocessing by speech processor 106 as described in further detail below.The output of speech processor 108 is then communicated by gateway 106to the appropriate destination packet network.

Referring now to FIG. 2, a block diagram of an illustrativemulti-channel speech processor 208, in accordance with one embodiment ofthe present invention, is shown. Speech processor 208 corresponds tospeech processor 108 of FIG. 1, and comprises at least one controller210 executing a complexity resource manager (CRM) 212. The controller210 is coupled for communication to a memory 214 and one or more signalprocessing units (SPU) 216 and receives and transmits information via aplurality of input/output channels 224 to other systems or devices.

Controller 210 comprises a processor, such an ARM® microprocessor, forexample. In certain embodiments, a plurality of controllers 210 may beused to enhance the speech processor's 208 performance or to providegreater channel density. Similarly, a plurality of SPUs 216 may be usedto provide increased performance and/or channel density of speechprocessor 208.

Memory 214 stores information accessed by controller 210 and SPU 216. Inparticular, memory 214 stores speech signal process time values in astatistical data table 218 or other database format which is used tocalculate a complexity budget by CRM 212 as described more fully below.For example, the statistical data table 218 may record the speech signalprocess time spent by speech processor 208 to encode the speech frameson each communication channel. In this way, CRM 212 is able to determinethe remaining process time available to process the remaining channels(i.e., the remaining complexity budget). An illustration for carryingout this calculation is described more fully below. Memory 214 alsostores speech signal data which is processed by SPU 216 as well as thepacketized speech data after conversion by SPU 216.

It is noted that the arrangement of speech processor 200, as depicted inFIG. 2, is only illustrative and other arrangement for carrying out theoperations of CRM 212 are suitable for use with present invention. Forexample, a clock of controller 210 may be used to measure the trueexecution time. In that case, all of the timing information will beproduced by controller 210, and not shared in memory 214 with SPU 216.In other embodiments, the operations of CRM 212 may be carried outcompletely in SPU 216. In yet other arrangements, the operations of CRM212 may be distributed between controller 210 and SPU 216.

SPU 216 carries out the operation of converting a given frame of speechsignal data from an input channel 224 into a packetized format using oneof the coding rates of a speech codec 220. For example, the SPU 216 mayuse one of the four SMV coding rates (e.g., full rate, half rate,quarter rate, and eighth rate) to convert a speech signal frame receivedvia input channels 224. The determination as to which coding rate theSPU 216 uses for this encoding process is carried out by CRM 212 inaccordance with the present invention and, if desired, in conjunctionwith other speech encoder algorithms.

CRM 212 typically comprises software, which is executed by controller210 to control the overall multi-channel processing complexity of speechprocessor 208 by signaling SPU 216 to perform its encoding operation ina complexity-reduced mode (i.e., use a less complex coding rate or aless complex version of one or more blocks of the coding scheme) basedon the calculated complexity budget under certain conditions. Thisscheme allows CRM 212 to sacrifice the average bit rate and/or qualityof certain channels per cycle, when required, to satisfy the complexitybudget, thereby providing greater channel density under certainconditions. Such conditions may include situations where a high numberof channels are carrying active speech. However, this temporary decreasein quality for most speech codecs is not normally detectible by theuser, partly because bursts of high number of channels at activecondition are only transitory, and partly because the order in whichchannels are processed by SPU 216 may not necessarily sequential, andtherefore the same channel may not necessarily be sacrificed overextended periods or over consecutive processing cycles. In someembodiments, channels may be processed sequentially, but in otherembodiments channels may be processed randomly. In the case of SMV, thefull rate coder, which might be less complex than the half rate coder(i.e., requires less processing time), is of better quality than thehalf rate. In this case, the use of the less complex full rate for thereduction of the complexity would not result in a reduction of quality,and the only impact on the system would be a slight increase in theaverage bit rate. Since the transient increase of the average bit ratehas only minimal impact on the performance of the communication channelsimplemented in the packet networks 110 of FIG. 1, this increase will notbe felt by the end user and will not have a significant impact on thesystem performance. As a result, a higher channel density may befacilitated by the speech processor 208 of the present invention withlittle or no appreciable quality loss from a user's perspective.

In conjunction with CRM 212, controller 210 may also execute otherspeech processing algorithms to further enhance the speech encodingperformance. These other speech encoding algorithms may be implementedin conjunction with CRM 212 or integrated directly within CRM 212. Forexample, higher complexity encoders may be selected to encode activespeech segments, while lower complexity encoders may be used to processsilence or background noise (inactive speech) segments to efficientlyallocate processing power. However, also as noted above, there may beinstances where a majority or all channels involve active speech.Normally, speech encoder algorithms would select higher complexitycoding rates to encode the signals associated with the active speechchannels. Yet, in accordance with the present invention, CRM 212 maydefine a lower complexity rate than the encoder algorithm in accordancewith the complexity budget. When this occurs, the coding rate selectedby CRM 212 overrides the coding rate selected by the encoder algorithm.When CRM 212 does not define a coding rate (e.g., where the complexitybudget would allow the remaining channels to be processed at the highestcomplexity coding rate) or where the coding rate selected by the encoderalgorithm is of less complexity than the coding rate defined by CRM 212(e.g., where the speech signal is an inactive speech segment), thecoding rate selected by the encoder algorithm is used by SPU 216 toprocess a given speech signal. However, when CRM 212 does define acoding rate (e.g., where the complexity budget would not allow theremaining channels to be processed at the highest complexity codingrate), the lower coding rate selected by CRM 212 overrides the codingrate selected by the encoder algorithm to process a given speech signal.

Referring next to FIG. 3, there is shown an illustrative flow diagram ofa speech encoding method utilizing CRM 212 in accordance with oneembodiment of the present invention. To illustrate this process,reference will be made to an example speech processor 208 having four(4) SPUs 216. In this example, speech processor 208 is configured tosupport sixty (60) communication channels (each SPU 216 processingfifteen (15) channels). To further assist in illustrating the managementprocess of the present invention, the following exemplary specificationsare also provided: a processing power of 300 MIPS per frame cycle willbe defined for each SPU 216; the exemplary four rates of the SMV codecwill be referenced (full rate, half rate, ququarter rate, or eighthrate); and Table 1 defines exemplary peak complexity values associatedwith the SMV coding rates.

TABLE 1 Rate Processing Power Full rate 15 MIPS Half rate 25 MIPSQuarter rate 10 MIPS Eighth rate  5 MIPS

As noted above, the SMV half rate is the rate of highest complexity (25MIPS (million instructions per second)) due to the complex searches usedduring encoding a half rate packet. In other implementations, ratherthan complexity rates, “complexity blocks” having associated levels ofcomplexity may be used and selected by CRM 212 for selecting the levelof encoding by SPUs 216. The complexity blocks define a complexity levelof encoding to be used by SPU 216.

Referring now FIG. 3, as well as FIGS. 1 and 2, process 300 is carriedout by speech processor 208 every frame cycle (e.g., every 20 ms) toprocess speech signals from packet network 102. In the present example,the speech signal frame segments from the 60 channels are processed bythe 4 SPUs 216, each SPU 216 processing 15 speech signal frame segments.The following discussion relates to the process carried out by one ofthe SPU 216, although a similar process is carried out by the remainingSPUs.

First at block 302, the speech signal time values stored in statisticaldata table 218 are reset. This reset occurs during startup and at thebeginning of each frame cycle. Next at block 304, the speech signalframe segment for the first channel is received. As noted above, theactual order in which channels are processed may not be defined in anyparticular sequence; thus, “first channel” relates to the channel whichis processed first, rather than the channel in the first position. Atthis point, there is no historical speech signal time values stored instatistical data table 218; and therefore, the speech signal framesegment is passed to SPU 216 for processing (normally from memory 214).

At block 306, the speech signal frame segment from block 304 isprocessed by SPU 216, based on the input speech. As described above, oneor more speech encoder algorithms may be used to define the coding rateused to encode the input speech (e.g., based on active or inactivespeech).

At block 308, the time spent processing the speech signal frame segmentduring block 306 is recorded or otherwise stored in statistical datatable 218. This time value represents the process time consumed duringthe encoding operation of block 306 (“speech signal process timevalue”). Using the example values from Table 1, if the full rateencoding scheme was used, about 15 MIPS might have been consumed; if thehalf rate encoding scheme was used, about 25 MIPS might have beenconsumed; and so on. It is noted that the time recorded can be eithertrue time measurements, obtained by the system clock, or pre-tabulatedvalues. The pre-tabulated values might be, for example, pre-measuredmaximum execution time for each rate.

At block 310, the next channel speech signal frame is then received forprocessing. Next at block 312, CRM 212 evaluates statistical data table218 and calculates a complexity budget. As described above, thiscalculation can be made at certain intervals (or groupings). Since eachSPU 216 processes fifteen (15) speech frame in this example, thisevaluation/calculation can be made after five (5) channels have beenprocessed, and again after ten (10) channels have been processed (wherethe 15 channels are grouped into three groups of five channels). It isnoted that other grouping and combinations may be used. In certainembodiments, the evaluation/calculation can be made in accordance with adynamic or intelligent scheme, rather than at fixed intervals. In yetother embodiments, the evaluation/calculation can be made any time afterthe first channel has been processed.

One way to determine the remaining complexity budget would be tosubtract the consumed process time from the available process time. Byway of example, suppose the first five (5) channels were processed usingthe SMV half rate. In this case, statistical data table 218 mightindicate that 125 MIPS have been consumed (5 channels, each consuming 25MIPS for the half rate). Accordingly, CRM 212 would calculate that theremaining complexity budget to be 175 MIPS (125 MIPS consumed from the300 MIPS of processing power).

At decision block 314, CRM 212 then determines the complexity codingrate at which the remaining channels can be processed based on thecalculated complexity budget from block 312. For example, CRM 212 maydetermine the “highest” complexity coding rate at which the remainingchannels can be processed. If the highest complexity coding rate issuitable for use based on the complexity budget, processing continues toblock 324 as indicated by connection “B” 318. If not, CRM 212 mayevaluate whether the next “highest” complexity coder is suitable; and soon. Where CRM 212 determines a reduced coding is appropriate for usebased on the complexity budget, processing continues to block 320 asindicated by connection “A” 316.

Using the exemplary values discussed above in conjunction with block212, CRM 212 has determined that after processing five (5) channels, theremaining complexity budget is 175 MIPS. Since there are ten (10)channels left to process, CRM 212 then determines that the remaining ten(10) channels may not be processed with the highest complexity codingrate (e.g., the SMV half rate), since the amount of processing time toprocess the remaining 10 channels at the half rate would require 250MIPS (ten channels at 25 MIPS). However, the next highest complexitycoding rate (i.e., the full rate) is suitable for use, since, at most,the amount of processing time to process the remaining ten channels atthe full rate would require 150 MIPS (ten channels at 15 MIPS). CRM 212may alternatively determine that one of the other lower complexity rates(quarter rate and eighth rate) may be used (e.g., to compensate for thebit rate usage). For example, a “complexity-reduced” SMV half-ratehaving an approximate processing complexity of 17 MIPS may alternativelybe used instead of the SMV full-rate. This complexity-reduced SMVhalf-rate would be suitable for use in the above example since, at most,the amount of processing time to process the remaining ten channelswould require 170 MIPS (ten channels at 17 MIPS) where the remainingcomplexity budget is 175 MIPS.

Now suppose that the first five (5) channels were processed at the halfrate and the next five (5) channels were processed at the full rate. Inthis case, the statistical data table 218 would indicate that 200 MIPShave been consumed (the first five (5) channels consuming 125 MIPS atthe half rate, and the next five (5) channels consuming 75 MIPS at thefull rate). Thus, CRM 212 would calculate that the remaining complexitybudget to be 100 MIPS (200 MIPS consumed from the 300 MIPS). With 100MIPS remaining, there would not be sufficient processing time to processthe remaining five (5) channels at the half rate, since 125 MIPS wouldbe needed at the half-rate. CRM 212 may then reduce the complexitycoding rate for the some or all of the remaining channels in order tocomply with the complexity budget as described above. As can be seenfrom this example, even though the highest complexity rate (half rate)was not available for use with all the channels, processing power wasmade available for all fifteen (15) channels for a given SPU (and thussupport for all sixty (60) channels considering the four SPUs 212).

At block 324, the speech signal frame segment is processed in an“unconstrained” manner. That is, CRM 212 does not provide an overridingcomplexity coding rate to use since the calculated complexity budgetwould allow processing at the highest complexity coding rate. In thiscase, the speech signal frame segment is processed based on the inputspeech in a manner similar to that described above in conjunction withblock 306. Block 326 is then carried out.

At block 320, CRM 212 reduces the complexity coding rate used by SPU212. For example, CRM 212 may signal SPU 212 to use the full rate (at 15MIPS) rather than the half rate (at 25 MIPS). As described above, thisless complex coding rate may be defined by CRM 212 to be used with justthe present channel or for a group of channels.

At block 322, SPU 212 processes the speech signal frame segment inaccordance with the complexity-reduced coding rate defined at block 320.As described above, speech encoder algorithms may be used in conjunctionwith CRM 212 to further optimize speech signal processing. Thus, theremay be cases where the speech encoder algorithm selects a lowercomplexity coding rate to be used for the present channel (e.g., forinactive speech) than the coding rate defined by CRM 212 at block 320.In this case, the speech signal frame segment is processed with thelower complexity coding rate selected by the speech encoder algorithm.Where the speech encoder algorithm selects a higher complexity codingrate to be used for the present channel (e.g., for active speech) thanthe coding rate defined by CRM 212 at block 320, the coding rate definedby CRM 212 overrides the coding rate selected by the speech encoderalgorithm, and SPU 216 processes the speech signal frame segment inaccordance with the complexity-reduced rate defined by CRM 212 at block320. Block 326 is then carried out.

At block 326, the time required to process the speech signal framesegment during block 322 or 324 is recorded in or otherwise cumulated tostatistical data table 218. As described above, this time valuerepresents process time consumed during the encoding operation of block322 or 324.

At decision block 328, CRM 212 then determines whether there are anymore channels to be processed by SPU 216 for the current cycle. If thereare additional channels to process, block 310 is repeated as indicatedby connection “C” 330. Otherwise, the next frame cycle is processed asdescribed above and block 302 is then carried out as indicated byconnection “D” 332.

Referring now to FIG. 4, an illustrative flow diagram 400 of a speechencoding method supporting variable communication channels in accordancewith one embodiment is shown. In this embodiment, speech processor 208is capable of interfacing with a variable or dynamic number ofcommunication channels, and determines whether a requested channel maybe supported based on a calculated complexity budget.

At block 410, speech processor 208 receives a request to manage a speechsignal for a channel (“requested channel”). Speech processor 208 may ormay not be managing other channels at this time.

At block 420, CRM 212 evaluates statistical data table 218 andcalculates a complexity budget. As described above, one way to determinethe remaining complexity budget would be to subtract the consumedprocess time from the available process time for the present cycle.

At decision block 430, CRM 212 then determines whether the requestingchannel can be supported based on the calculated complexity budgetdetermined during block 420. Various criteria may be used to definewhether the requested channel may be supported including, for example,the impact on quality and/or bit rate for one or more of the currentlyaccepted or active channels. In some embodiments, a pre-determinednumber of channels are supported. In this embodiment, CRM 212 willaccept a channel if the pre-determined number of channels have not beenexceeded (i.e., CRM 212 is currently managing fewer than thepredetermined number of channels). Otherwise, CRM 212 will reject therequested channel. In other embodiments, acceptance of a requestedchannel involves first determining whether SPU 216 is able to runwithout any complexity reduction (e.g., up to N channels). If so, CRM212 does not operate, and any requested channel can be accepted until Nchannels have been accepted. For each requested channel above Nchannels, CRM 212 performs statistical complexity reduction analysis.For example, CRM 212 may determine the level of complexity reductionneeded to accommodate the requested channel, and may accept/reject therequested channel based on whether a certain threshold of complexityreduction will be exceeded.

If the requested channel can be supported, block 440 is carried totransmit an “accept” reply and to process the speech signal from therequesting channel. Next at block 450, the requested channel is addedfor processing by the CRM 212 along with the other accepted channels. Ifnecessary, the coding complexity of the remaining channels to beprocessed may be adjusted in accordance with the method described abovein conjunction with FIG. 3. If the requested channel cannot besupported, block 460 is carried out to transmit a “deny” reply or otherrejection signal. Block 470 is then carried out to process the remainingaccepted or active channels. The process for encoding the active oraccepted channels are carried out as described above in conjunction withFIG. 3.

The methods and systems presented above may reside in software,hardware, or firmware on the device, which can be implemented on amicroprocessor, digital signal processor, application specific IC, orfield programmable gate array (“FPGA”), or any combination thereof,without departing from the spirit of the invention. Furthermore, thepresent invention may be embodied in other specific forms withoutdeparting from its spirit or essential characteristics. The describedembodiments are to be considered in all respects only as illustrativeand not restrictive.

What is claimed is:
 1. A multi-channel speech processor configured to process speech signals from a plurality of communication channels within a time budget, said multi-channel speech processor comprising: a controller capable of interfacing with said plurality of communication channels; a complexity resource manager (CRM) executed by said controller configured to process each of said communication channels and determine an amount of time spent for processing each of said communication channels; a memory coupled to said controller configured to store speech signal process time values, wherein said speech signal process time values are indicative of said amounts of time spent; and at least one signal processing unit (SPU) coupled to said memory and to said controller, said SPU configured to encode said speech signals; wherein said CRM is further configured to calculate a total amount of time spent for processing one or more of said communication channels using said speech signal process time values, determine a remaining time budget based on said total amount of time spent and said time budget, and signal said SPU to modify a coding rate of said SPU based on said remaining time budget.
 2. The speech processor of claim 1, wherein said SPU is further configured to encode said speech signals using one of plurality of coding rates of a speech coder, at least two of said coding rates having differing levels of complexity.
 3. The speech processor of claim 2, wherein said modified coding rate is of lower complexity from said at least two coding rates of differing levels of complexity.
 4. The speech processor of claim 3, wherein said CRM signals said SPU to modify said coding rate only when said remaining time budget is not sufficient for said SPU to encode remaining communication channels using a coding rate of higher complexity from said at least two coding rates of differing levels of complexity.
 5. The speech processor of claim 2, further comprising a speech encoder algorithm executed by said SPU, said speech encoder algorithm selecting one of said coding rates to be executed by said SPU for a given input speech signal based on said input speech signal.
 6. The speech encoder of claim 5, wherein said modified coding rate is a coding rate of lower complexity, as selected by said CRM, from said at least two coding rates of differing levels of complexity, said coding rate selected by said CRM overrides said coding rate selected by said speech encoder algorithm.
 7. The speech encoder of claim 6, wherein said CRM signals said SPU to modify said coding rate only when said remaining time budget is not sufficient for said SPU to encode remaining communication channels using a coding rate of higher complexity from said at least two coding rates of differing levels of complexity.
 8. The speech processor of claim 1, wherein said SPU encodes said speech signal using one of a plurality of coding rates from the selectable mode vocoder (SMV) coder.
 9. The speech processor of claim 1, wherein said SPU encodes said speech signal using one of a plurality of coding rates from the enhanced variable rate speech coder (EVR) codec.
 10. The speech processor of claim 1, wherein said SPU encodes said speech signal using one of a plurality of coding rates from the adaptive multi-rate (AMR) coder.
 11. The speech processor of claim 1, wherein said SPU encodes said speech signal using one of a plurality of coding blocks having different levels of complexity.
 12. A multi-channel speech processor configured to process speech signals from a plurality of communication channels within a time budget, said multi-channel speech processor comprising: a controller capable of interfacing with a variable number of said plurality of communication channels; a complexity resource manager (CRM) executed by said controller configured to process each of said communication channels and determine an amount of time spent for processing each of said communication channels; a memory coupled to said controller configured to store speech signal process time values, wherein said speech signal process time values are indicative of said amounts of time spent; and at least one signal processing unit (SPU) coupled to said memory and to said controller, said SPU configured to encode said speech signals; wherein said CRM is further configured to: receive a request to process speech signals from a new communication channel, calculate a total amount of time spent for processing one or more of said communication channels, until receiving said request, using said speech signal process time values, determine a remaining time budget based on said total amount of time spent and said time budget, transmit an accept reply in response to said request if said new communication channel and said remaining communication channels can be processed within said remaining time budget.
 13. The speech processor of claim 12, wherein said CRM is further configured to: transmit a deny reply in response to said request if said new communication channel and said remaining communication channels cannot be processed within said remaining time budget.
 14. The speech processing unit of claim 12, wherein a coding rate of said SPU is modified to process said new communication channel and said remaining communication channels within said remaining time budget. 